We collected the data from a Scania autonomous bus platform mounted with two lidars and two front facing cameras for a route length of \(\approx \) 1.5 Kms. The ground truth (GT) curb features are provided by a map supplier. All the sensing data was synchronized using PTP (Precision Time Protocol) synchronization and converted to rosbags for evaluation. We evaluated the generated curb points by manually selecting the corresponding GT curb points. The point cloud selection tool for association was developed using open3d [1]}. Since manual association is a tedious process we also propose a mechanism for automatic evaluation of the clusters. The clustering algorithms are evaluated offline from scikit-learn [2]} package.
